Simple and objective prediction of survival in patients with lung cancer: staging the host systemic inflammatory response

Background. Prediction of survival in patients diagnosed with lung cancer remains problematical. The aim of the present study was to examine the clinical utility of an established objective marker of the systemic inflammatory response, the Glasgow Prognostic Score, as the basis of risk stratification in patients with lung cancer. Methods. Between 2005 and 2008 all newly diagnosed lung cancer patients coming through the multidisciplinary meetings (MDTs) of four Scottish centres were included in the study. The details of 882 patients with a confirmed new diagnosis of any subtype or stage of lung cancer were collected prospectively. Results. The median survival was 5.6 months (IQR 4.8–6.5). Survival analysis was undertaken in three separate groups based on mGPS score. In the mGPS 0 group the most highly predictive factors were performance status, weight loss, stage of NSCLC, and palliative treatment offered. In the mGPS 1 group performance status, stage of NSCLC, and radical treatment offered were significant. In the mGPS 2 group only performance status and weight loss were statistically significant. Discussion. This present study confirms previous work supporting the use of mGPS in predicting cancer survival; however, it goes further by showing how it might be used to provide more objective risk stratification in patients diagnosed with lung cancer

Vermonters’ Opinions on Low-Dose CT Lung Cancer Screening

Introduction: Lung cancer is the number one cause of cancer death among men and women in Vermont and the United States. Smoking increases the risk of lung cancer—nearly 90% of lung cancer is due to smoking. Frequently, lung cancers do not present clinically until they are advanced stage and therefore prognosis is poor. However, if detected early lung cancers are more operable and patients have better outcomes. In December 2013 the US Preventive Services Task Force released new guidelines for lung cancer screening among current and former smokers ages 55 to 80. It is recommended that current and former (within 15 years of quitting) smokers of 30 pack years receive an annual low-dose CT scan. The objective of this project was to assess the level of knowledge and attitudes towards lung cancer screening with low-dose CT scanning among Vermonters in the Burlington area.https://scholarworks.uvm.edu/comphp_gallery/1205/thumbnail.jp

Unlocking biomarker discovery: Large scale application of aptamer proteomic technology for early detection of lung cancer

Lung cancer is the leading cause of cancer deaths, because ~84% of cases are diagnosed at an advanced stage. Worldwide in 2008, ~1.5 million people were diagnosed and ~1.3 million died – a survival rate unchanged since 1960. However, patients diagnosed at an early stage and have surgery experience an 86% overall 5-year survival. New diagnostics are therefore needed to identify lung cancer at this stage. Here we present the first large scale clinical use of aptamers to discover blood protein biomarkers in disease with our breakthrough proteomic technology. This multi-center case-control study was conducted in archived samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC) in long-term tobacco-exposed populations. We measured >800 proteins in 15uL of serum, identified 44 candidate biomarkers, and developed a 12-protein panel that distinguished NSCLC from controls with 91% sensitivity and 84% specificity in a training set and 89% sensitivity and 83% specificity in a blinded, independent verification set. Performance was similar for early and late stage NSCLC. This is a significant advance in proteomics in an area of high clinical need

Patterns of CT lung injury and toxicity after stereotactic radiotherapy delivered with helical tomotherapy in early stage medically inoperable NSCLC

To evaluate toxicity and patterns of radiologic lung injury on CT images after hypofractionated image-guided stereotactic body radiotherapy (SBRT) delivered with helical tomotherapy (HT) in medically early stage inoperable non-small-cell lung cancer (NSCLC)

Independent Weighted Feature Set with Linked Feature Reduction Model for Lung Cancer Stage Detection using Machine Learning Model

Lung cancer is a potentially fatal disease that is affected to 18% of population every year. Finding the exact location of a cancer and identification of lung cancer stage continues to be difficult for medical professionals. The true reason for cancer and a comprehensive cure is still unknown. Treatment for cancer is possible if detected at an early stage with accurate stage detection. Finding areas of the lung that have been impacted by cancer requires the use of image processing techniques like noise reduction, highlight filtration, recognizable proof of effected lung regions, and perhaps a comparison with data on the curative history of lung cancer. This research investigates whether or not technology enabled by machine learning algorithms and image processing can correctly classifies and predict lung cancer. For images, the dimensional feature channel is used in the preliminary processing stage. The proposed model considers Magnetic Resonance Imaging (MRI) images for detection of lung cancer. This research proposes an Independent Weighted Feature Set with Linked Feature Reduction (IWFS-LFR) model for accurate lung cancer stage detection based on the size of the tumour. The tumour stage can be accurately predicted using the feature attribute similarity calculation for accurate detection of lung cancer stage for proper diagnosis. The proposed model when contrasted with the traditional model exhibits better performance

ANN for Predicting DNA Lung Cancer

Abstract: Lung cancer is the top reason of cancer-associated deaths globally. Surgery is the typical treatment for early-stage non-small cell lung cancer (NSCLC). Advancement in the knowledge of the biology of non-small cell lung cancer has shown molecular evidence used for systemic cancer therapy aiming metastatic disease, with a significant impact on patients’ overall survival (OS) and eminence of life. Though, a biopsy of overt metastases is an invasive technique restricted to assured positions and not effortlessly satisfactory in the clinic. The examination of peripheral blood samples of cancer patients embodies a new basis of cancer-derived material, recognized as liquid biopsy, and its constituents (circulating tumour cells (CTCS), circulating free DNA (cfDNA), exosomes, and tumour-educated platelets (TEP)) may be gotten from nearly any body liquids. These constituents have shown to imitate features of the status of both the primary and metastatic diseases, aiding the clinicians to go towards a tailored medicine. In this paper, the reasons of lung cancer will be recognized and the risk elements that initiated the increase of infection, for instance Smoking, Disclosure to secondhand smoke, Disclosure to radon gas, Disclosure to asbestos and other compounds, Family past history of lung cancer, and decrease of the spread of disease and approaches of handling and prevention of lung cancer

Epithelial cell migration as a potential therapeutic target in early lung cancer.

Lung cancer is the most lethal cancer type worldwide, with the majority of patients presenting with advanced stage disease. Targeting early stage disease pathogenesis would allow dramatic improvements in lung cancer patient survival. Recently, cell migration has been shown to be an integral process in early lung cancer ontogeny, with preinvasive lung cancer cells shown to migrate across normal epithelium prior to developing into invasive disease. TP53 mutations are the most abundant mutations in human nonsmall cell lung cancers and have been shown to increase cell migration via regulation of Rho-GTPase protein activity. In this review, we explore the possibility of targeting TP53-mediated Rho-GTPase activity in early lung cancer and the opportunities for translating this preclinical research into effective therapies for early stage lung cancer patients

Lung Cancer Care Before and After Medicare Eligibility.

Uninsured and underinsured near-elderly may not have timely investigation, diagnosis, or care of cancer. Prior studies suggest Medicare eligibility confers significant and substantial reductions in mortality and increases in health service utilization. We compared 2245 patients diagnosed with lung cancer at ages 64.5 to 65 years and 2512 patients aged 65 to 65.5 years, with 2492 patients aged 65.5 to 66 years (controls) in 2000 to 2005. Compared with controls, patients diagnosed with lung cancer before Medicare eligibility had no statistically significant differences in cancer stage, time to treatment, type of treatment, and survival. Study power was sufficient to exclude mortality reductions and health service utilization changes of the magnitude found in prior work, suggesting that typically, appropriate lung cancer care may be sought and delivered regardless of insurance status